1. Technical Field
The present invention relates to a signal transmission device for transmitting a digital signal consisting of continuous words, such as a PCM signal, obtained by digitizing an analog signal by blocking it for a predetermined number of words, and more particularly to a signal transmission device for transmitting a digital signal by obtaining a predicted error for each block and quantizing the predicted error.
2. Background Art
The general construction of a prior art device is shown in FIG. 8. The device consists of a coding processing system 10 on the transmission (or recording) side and a decoding processing system 20 on the reception (or reproducing) side. The input terminal 11 of the coding processing system 10 is supplied with an input signal x.sub.n, which, for example, is an audio PCM signal obtained by sampling an analog audio signal at a frequency f.sub.s and subjecting it to quantization and coding. The difference between the true input signal x.sub.n and a predicted value X.sub.n from a prediction unit 13 is obtained by a subtractor 12. The prediction unit may be, for example, as shown in FIG. 10, a device which consists of two delay units 31 and 32 for delaying input data by one sampling cycle, two multipliers 33 and 34 for multiplying the data delayed by the delay units 31 and 32 by predetermined coefficients K and K.sub.2, respectively, and an adder 35 for summing the results of multiplication. The output data of the adder 35 is the predicted value X.sub.n. The difference output .delta..sub.n from subtractor 12 is quantized in an adaptive quantizer 14 into a quantized value Q.sub.n which is transmitted via an output terminal 15 toward the decoding processing system 20, and is supplied to an adaptive inverse quantizer 16. The quantized value Q.sub.n supplied to the adaptive inverse quantizer 16 is added with a quantization error q.sub.n to become an inverse quantized value .delta.'.sub.n. The inverse quantized value .delta.'.sub.n is added with the aforementioned predicted value X.sub.n in an adder 17, and is supplied to the prediction unit 13 as an input value X.sub.n. A predicted value X.sub.n+1 output from the prediction unit 13 based on the input value X.sub.n serves as the predicted value for the next input signal X.sub.n+1.
In the decoding processing system 20, the quantized value Q.sub.n transmitted from the coding processing system 10 is supplied to an input terminal 21 and is converted to an inverse quantized value .delta.'.sub.n, in an adaptive inverse quantizer 22 by being added with the quantization error q.sub.n, and is further added in adder 23 with the predicted value X.sub.n from a prediction unit 24. The sum X.sub.n is used as an input value to the prediction unit 24 and is applied as an output at output terminal 25 as a decoded signal. The decoding processing system 20 has a construction which is the same as the construction of the latter half of the coding processing system 10 (adaptive inverse quantization unit 16, adder 17, and prediction unit 13).
Next, referring to FIG. 9, which shows actual signal values, the operation of a circuit with the above construction will be described.
First, assume that the input value and its predicted value at a point n on the time axis are X.sub.n and X.sub.n, respectively, and their difference is called the predicted error .delta..sub.n. Namely, EQU .delta..sub.n =X.sub.n -X.sub.n ( 1)
The predicted error .delta..sub.n is input to an adaptive quantizer Q.sub.n and bit-compressed to, for example, a quantized value Q.sub.n with 4 bits (-8 to +7). By inputting the quantized value Q.sub.n to the adaptive inverse quantizer 16, its output, namely, the inverse quantized value .delta..sub.n, represents the sum of the predicted error .delta..sub.n and the quantization error q.sub.n. In other words the equation EQU .delta..sub.n '=.delta..sub.n +q.sub.n ( 2)
holds true for situations where the output value is greater than the input value (i.e., sample point n+1 in FIG. 9). However, the equation .delta..sub.n =.delta.'.sub.n +q.sub.n holds true for situations where the output value is less than the input value (i.e., sample point n). Further, the sum of the inverse quantized value .delta..sub.n ' and the aforementioned predicted value X.sub.n becomes the input value X.sub.n to the prediction unit 13, namely, EQU X.sub.n =.delta..sub.n '+X.sub.n ( 3)
On the other hand, the value X.sub.n is the sum of the input value X.sub.n and the quantization error q.sub.n as is clear from FIG. 9. That is, EQU X.sub.n =X.sub.n +q.sub.n ( 4)
Note that the above result can also be obtained from equations (1)-(3).
By constructing the decoding processing system 20 to be the same as the latter half of the coding processing system 10, it becomes possible to derive the input value X.sub.n in the prediction unit 24 as a decoded signal. Further, the predicted value X.sub.n+1 for the time point (n+1) will be given as the output value of the prediction unit 24 based on the input value X.sub.n. Thus it can be seen that the predicted value for any sample time is based on the prior
sample value and therefore the size of .delta..sub.n depends partly on the change in sample values from one sample period to the next.
Signal transmission is carried out by the repetition of the above-mentioned operations, and, for example, decoded output values shown by the broken line in FIG. 9 are obtained for input values as shown by the solid line.
The quantization width (range identified by the arrows in FIG. 9) in the adaptive quantizer 14 and adaptive inverse quantizer 16 varies adaptively in response to the magnitude of the absolute value ( Q.sub.n ) of the quantized value Q.sub.n for the preceding cycle. 9).
In this case, the quantized value Q.sub.n is obtained by subjecting a difference between the input value X.sub.n and the predicted value X.sub.n to the quantization, and more particularly, the predicted value X.sub.n is obtained by averaging the values of X.sub.n-1 and X.sub.n-2 after multiplying each by a coefficient. When the quantized value Q.sub.n is small an input X.sub.n newly applied is approximately equal to the average of the previous two inputs X.sub.n-1 and X.sub.n-2 that have been applied thereto. In other words, there is no abrupt change in an input signal at the sampling point n. In contrast, in the case of the quantized value Q being large, there is an abrupt change in the input signal at the sampling point n. Accordingly, the quantization width in the following cycle is varied in response to the absolute value ( Q.sub.n ) of the quantized value Q.sub.n, so that it is possible to detect the variation in the input signal with the small number of bits, 4 bits for example.
In order to realize the above, the adaptive quantizer 14 and the adaptive inverse quantizers 16 and 22 are provided with coefficient multipliers to vary the quantization width in response to the absolute value ( Q.sub.n ). A concrete example thereof will be described.
The quantization width (range identified by the arrows in FIG. 9) in the adaptive quantizer 14 and adaptive inverse quantizer 16 varies adaptively in response to the magnitude of the absolute value ( Q.sub.n ) of the quantized value Q.sub.n for the preceding cycle. 9).
As an example of the adaptive variation of the quantization, when Q.sub.n is 4 bits, the quantization width at the point (n+1) is obtained by the product of the following constant K and the quantization width at the point (n). Accordingly, it can be varied adaptively.
______________________________________ Absolute value of Q.sub.n Constant K ______________________________________ 0 0.84 1 0.84 2 0.92 3 0.92 4 1.00 5 1.3 6 1.69 7 2.39 ______________________________________
Because of this, the quantization error q.sub.n varies with the magnitude of the change in signal, and a more faithful transmission signal becomes possible.
In the prior art device described above, the construction is such that as the frequency of the input signal is increased, the difference between the neighboring sample values is large and the predicted error .delta..sub.n and its quantized value .delta..sub.n ' becomes correspondingly large, with a result that the quantization step width becomes large and the quantization error q.sub.n becomes correspondingly large. Consequently, the distortion factor of the decoded value X.sub.n increases.
FIG. 11 depicts the frequency versus distortion characteristic of the signal transmission device.
In contrast to the case of a PCM signal with the same quantization bit number m, where a band in the vicinity of f.sub.s /2, (f.sub.s is the sampling frequency)is available, the band width is narrowed down considerably in the present case if the distortion factor is to be equal to or smaller than the distortion factor of the system using constant quantization level m.
Further, in the prior art device there occurs the so-called slope overflow for a sudden change in the input signal. Namely, when a value exceeding the quantization width indicated by the arrows in FIG. 9 is input, the decoded signal (broken line) cannot follow the input signal (solid line) as shown in FIG. 12, and the distortion is increased.